In conventional data analysis tools, it can be difficult for analysts and business users to know what the best next step to take is or decision to make when navigating or exploring data. This feeling of being lost in the data results in a less powerful analysis experience, as well as a higher degree of frustration and, potentially, wasted time. Traditional data analysis tools provide representations of a snapshot in time for key performance indicators (KPIs) and value drivers that are used to analyze the state of set targets in analytical reporting. For example, in a conventional business report providing year to date (YTD) details about profit and expenses data, various accounting measures can be provided in a ‘bullet chart’ and other conventional representations. However, such representations are snapshots in time, and do not convey the performance of a plotted measures over the course of time. Conventional analytical and decision support reports merely convey ‘what has happened’ so far to data up to a point in time, rather than ‘how it happened’ across time intervals. Such reports are of limited help when an analyst tries to identify key patterns across time and space leading to the current state of the data.